The Dynamic Spread of Happiness in a Large Social Network

Background A broad range of stimuli to human happiness has been explored, but past studies have not addressed a possibly key stimulus to human happiness: the happiness of others. Objectives To evaluate whether happiness can spread from person to person and whether niches of happiness form within social networks. Design Longitudinal social network analysis. Setting Framingham Heart Study Social Network. Participants 4,739 individuals followed from 1983 to 2003. Main Outcome Measures We measured happiness using a validated four-item scale, and we ascertained a broad array of social network attributes as well as diverse social ties. Results Clusters of happy and unhappy people are visible in the network, and the relationship between people’s happiness appears to extend up to three degrees of separation (e.g., to one’s friends’ friends’ friends). People who are surrounded by many happy people and those who are central in the network are more likely to become happy in the future. Longitudinal statistical models suggest that happiness clusters result from the spread of happiness and not just a tendency for people to associate with similar individuals. A friend who lives within a mile and who becomes happy increase the probability a person is happy by 25% (95% C.I. 1% to 57%). Similar effects are seen in coresident spouses (8%, 0.2% to 16%), siblings who live within a mile (14%, 1% to 28%), and next-door neighbors (34%, 7% to 70%). Effects are not seen between co-workers. The effect decays with time and with geographic separation. Conclusions People’s happiness depends on the happiness of others to whom they are connected. This provides further justification for seeing happiness, like health, as a collective phenomenon.